Performing semantic analyses of user-generated textual and voice content

14) A method for performing semantic analysis on a user-generated text string, the method comprising:

• identifying a plurality of most-recurring topics from user-generated content obtained from a one or more data sources, wherein the user-generated content comprises a plurality of text strings;
• labeling the plurality of most-recurring topics as seed topics;
• extracting a plurality of contextually similar words associated with each of the seed topics, wherein the extracting comprises querying a neural network model;
• computing a relevance matrix based on a cosine distance between each of the plurality of contextually similar words and the plurality of text strings from the user-generated content;
• and
• performing a latent dirichlet allocation (LDA) operation using the relevance matrix as an input to obtain a distribution of issues related to the seed topics.

18) A system for extracting actionable topics from user-generated content, the system comprising:

• a first processing module communicably coupled to one or more content-generation systems, the first processing module being configured to obtain user-generated content from said one or more content-generation systems;
• a second processing module communicably coupled to the first processing module, the second processing module configured to:
• extract a location associated with the user-generated content, a time associated with the user-generated content, and an actionable topic associated with the user-generated content, wherein at least one of the location, the time, and the actionable topic are extracted by performing semantic analysis on a text string within the user-generated content;
• identify a remedial action based on the actionable topic;
• and
• transmit a recommendation to a service provider network associated with the actionable topic, wherein the recommendation comprises the identified remedial action, the location, and the time.